Course Taking Patterns and Pathways through STEM: A Case Study Using Individual-Level Institutional Data for Program Assessment

Motivated by assessment of externally awarded grants and internal programmatic practices, we used transcript and demographic data for students entering a highly selective residential liberal arts college between 2002-2015 to answer institutional-level questions about course taking patterns and pathways relevant to Science, Technology, Engineering, and Mathematics (STEM). We used transcript data to categorize a student's intention to major in STEM at three points: their first semester, at the end of sophomore year, and at graduation. Students took several paths toward graduation including complete persistence in STEM, early switching, late switching and double switching. Using this classification scheme, we investigated any potential gender effect or "new building effect" and compared participation in an integrated introductory chemistry and biology course sequence to traditional discipline-specific sequences. For students where self-reported data on intention existed, either from matriculation surveys or major declaration, we compared our transcript classification with self-reported interest in STEM. Relying solely on institutional level data provides an inclusive, unbiased analysis with minimal missing data.